Opposing Forces of Social Attraction and Social Avoidance Drive Network Modularity

Abstract

SUMMARY: How interactions between individuals contribute to the emergence of complex societies is a major question in biology. Nonetheless, little remains known about how simple rules of social attraction (e.g. to information) and social avoidance (e.g. of disease) interact to shape sociality. We developed an individual-based model where individuals choose with whom to interact depending on the status of group mates (informed and/or infected). Statistical models indicate that the emergence of social structure depends on the cost/benefit trade-offs underlying the system. Critically, pressures that optimize social relationships – i.e. minimize risky connections while favouring those that maximize benefits – yield modular networks. The most modular networks emerged when few individuals monopolized values of pathogen whereas information was more equally distributed across the group. We argue that investigating the mechanisms of such social trade-offs, simultaneously accounting for both attractive and repulsive forces acting on individuals, will help us understand the complexity of individual relationships.